Knowledge that Transforms

In a model of career concerns for experts, when is a principal hurt from observing more information about her agent? This paper introduces a distinction between information on the consequence of the agent’s action and information directly on the agent’s action. When the latter kind of information is available, the agent faces an incentive to disregard useful private signals and act according to how an able agent is expected to act a priori. This conformist behavior hurts the principal in two ways: the decision made by the agent is less likely to be the right one (discipline) and ex post it is more difficult to evaluate the agent’s ability (sorting). The paper identifies a necessary and sufficient condition on the agent signal structure under which transparency on action is detrimental to the principal. The paper also shows the existence of complementarities between transparency on action and transparency on consequence. The results on the distinction between transparency on action and transparency on consequence are then used to interpret existing disclosure policies in politics, corporate governance, and delegated There is a widespread perception, especially among economists, that transparency is a beneficial

We analyze the colonial land revenue institutions set up by the British in India, and show that differences in historical property rights institutions lead to sustained differences in economic outcomes. Areas in which proprietary rights in land were historically given to landlords have significantly lower agricultural investments and productivity in the post-independence period than areas in which these rights were given to the cultivators. These areas also have significantly lower investments in health and education. These differences are not driven by omitted variables or endogeneity problems; they probably arise because differences in historical institutions lead to very different policy choices.

Many programs reward or penalize schools based on students' average performance. Mean reversion is a potentially serious hindrance to the evaluation of such interventions. Chile's 900 Schools Program (P-900) allocated resources based on cutoffs in schools' mean test scores. This paper shows that transitory noise in average scores and mean reversion lead conventional estimation approaches to overstate the impacts of such programs. It further shows how a regressiondiscontinuity design can be used to control for reversion biases. It concludes that P-900 had significant effects on test score gains, albeit much smaller than is widely believed

We develop a positive theory of the adoption of child labor laws. Workers who compete with children in the labor market support a child labor ban, unless their own working children provide a large fraction of family income. Fertility decisions lock agents into specific political preferences, and multiple steady states can arise. The introduction of child labor laws can be triggered by skill-biased technological change, which induces parents to choose smaller families. The theory can account for the observation that, in Britain, regulations were first introduced after a period of rising wage inequality, and coincided with rapid fertility decline.

People may be surprised to notice certain regularities that hold in existing knowledge they have had for some time. That is, they may learn without getting new factual information. We argue that this can be partly explained by computational complexity. We show that, given a knowledge base, finding a small set of variables that obtain a certain value of R 2 is computationally hard, in the sense that this term is used in computer science. We discuss some of the implications of this result and of fact-free learning in general.

Welfare-Enhancing Technological Change and the Growth of Obesity by Darius Lakdawalla, Tomas Philipson and Jay Bhattacharya. Published in volume 95, issue 2, pages 253-257 of American Economic Review, May 2005

We investigate the market for news under two assumptions: that readers hold beliefs which they like to see confirmed, and that newspapers can slant stories toward these beliefs. We show that, on the topics where readers share common beliefs, one should not expect accuracy even from competitive media: competition results in lower prices, but common slanting toward reader biases. On topics where reader beliefs diverge (such as politically divisive issues), however, newspapers segment the market and slant toward extreme positions. Yet in the aggregate, a reader with access to all news sources could get an unbiased perspective. Generally speaking, reader heterogeneity is more important for accuracy in media than competition per se.

Our main goal is to quantify the returns to a career in the United States Congress. We specify a dynamic model of career decisions of a member of Congress andestimate this model using a newly collected dataset. Given estimates of the structural model, we assess reelection probabilities, estimate the effect of congressional experience on private and public sector wages, and quantify the value of a congressional seat. Moreover, we assess how an increase in the congressional wage or the imposition of term limits would affect the career decisions of politicians and the returns from a career in Congress.

Using data from the U.S. Decennial Census and the National Longitudinal Surveys, we find little evidence of differences in the return to schooling across racial and ethnic groups, even with attempts to control for ability and measurement error biases. While our point estimates are relatively similar across racial and ethnic groups, our conclusion is driven in part by relatively large standard errors. ; That said, we find no evidence that returns to schooling are lower for African Americans or Hispanics than for non-minorities. As a result, policies that increase education among the low-skilled have a good possibility of increasing economic well-being and reducing inequality. More generally, our analysis suggests further research is needed to better understand the nature of measurement error and ability bias across subgroups in order to fully understand potential heterogeneity in the return to schooling across the population.

Why the Apple Doesn't Fall Far: Understanding Intergenerational Transmission of Human Capital by Sandra E. Black, Paul J. Devereux and Kjell G. Salvanes. Published in volume 95, issue 1, pages 437-449 of American Economic Review, March 2005